The name is a bit obscure if you don't think in very generalized terms right out of the gate. It refers to a linear polynomial of multiple variables, which by definition must have the super simple form of:and then we just put the unknown and each derivative into that simple polynomial:except that now the are not just constants, but they can also depend on the argument (but not on or its derivatives).
Explicit solutions exist for the very specific cases of:
- constant coefficients, any degree. These were known for a long time, and are were studied when Ciro was at university in the University of São Paulo.
- degree 1 and any coefficient
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A scalar linear differential equation of order has the formHere the coefficients and the forcing term are prescribed functions of the independent variable . A classical solution of a differential equation is an -times differentiable function satisfying the identity at every point of its interval. The unknown function and its derivatives enter to the first power, without products between them or coefficients depending on . Equivalently, the differential operator is a linear map: for constant scalars ,The forcing term may be zero, giving a homogeneous linear differential equation, or nonzero, giving an inhomogeneous linear differential equation. Linearity of does not mean that every function graph of a solution of a differential equation is a straight line.
To use the usual order- initial value problem theory on an interval , assume that throughout and that all and are continuous functions there. Dividing by normalizes the highest derivative; specifying at then selects one solution of a differential equation throughout . A zero of needs separate analysis: one cannot divide through it and retain these conclusions. The first-order normalization appears in OpenStax's definition and standard form of linear equations; the corresponding system theorem is in MIT's existence and uniqueness notes for linear systems.
The coefficients need not be linear functions of . For example, is a linear differential equation on , although is quadratic. Its solution of a differential equation with initial condition is : its derivative is , so substitution gives , and . The zero of the highest coefficient at explains the domain restriction. In contrast, , and are nonlinear ordinary differential equations because of their dependence on the unknown function. Variable coefficients and nonlinear ordinary differential equations are different issues; see MIT's definitions and examples of first-order linear equations.
The practical benefit of linearity is that it separates the effect of the initial condition from the effect of the forcing term. Once one particular solution satisfies , every solution of a differential equation isHere is the kernel of a linear map, consisting of solutions of a differential equation to the associated homogeneous linear differential equation. Indeed, , and conversely . Thus the family for a fixed forcing term is an affine space obtained by translating . If is not identically zero, the zero function is absent, so this family is not a vector space under the usual operations on functions. This short argument explains why a general solution is a particular solution plus a homogeneous solution.